基于物联网的在线、智能调度方法的相关思考

物联网的飞速发展给生产调度系统带来了前所未有的机遇和挑战,数据的多源异构和连续涌入性、信息的透明性以及人、物料、设备、生产过程、产品等众多对象呈现出的连续动态存在性,这些新特征导致传统的调度优化方法难以适用。在已有研究的基础上,总结了物联网、调度优化方法以及基于情景的建模方法的研究现状和存在的问题,分析基于物联网的在线智能调度涉及到的问题及其特征,并提出其中的关键科学问题是基于情景的在线建模方法;提出该问题未来的研究目标为:针对物联网环境下调度对象状态的动态连续变化性,提供一种在线实时的智能优化调度方法,以最终实现调度优化过程的连续性以及调度优化决策的科学性、有效性和实用性;并详细阐述了未来关于基于情景的建模方法、基于情景的模型实时求解方法和基于情景的在线调度决策支持方法三方面的研究内容,为后续的深入研究做前期的思考和探索。     

Priority Rules for Multi‐Task Due‐Date Scheduling under Varying Processing Costs

We study the scheduling of multiple tasks under varying processing costs and derive a priority rule for optimal scheduling policies. Each task has a due date, and a non‐completion penalty cost is incurred if the task is not completely processed before its due date. We assume that the task arrival process is stochastic and the processing rate is capacitated. Our work is motivated by both traditional and emerging application domains, such as construction industry and freelance consulting industry. We establish the optimality of Shorter Slack time and Longer remaining Processing time (SSLP) principle that determines the priority among active tasks. Based on the derived structural properties, we also propose an effective cost‐balancing heuristic policy and demonstrate the efficacy of the proposed policy through extensive numerical experiments. We believe our results provide operators/managers valuable insights on how to devise effective service scheduling policies under varying costs.     

Ad hoc网络中基于拥塞的机会调度算法

无线多跳Ad hoc网络中的节点在业务发送过程中需要竞争共享信道,容易发生局部拥塞导致网络性能下降,而且节点内部采用的先入先出(FIFO)队列容易使队头出现阻塞现象,影响队列中后续分组的发送。为此提出了一种基于拥塞的机会调度算法,发送节点发送RTS帧时目标指向多个下一跳接收节点,这些节点在正确解码RTS帧后根据自身拥塞程度按一定概率依照调度优先级顺序发送CTS帧。仿真结果表明,该算法提高了网络端到端的饱和吞吐量和信道利用率,也提高了业务流之间的公平性。     

移动计算环境中的数据广播研究

在移动计算环境中,数据广播能支持大规模并发用户访问服务器上的数据,是提高移动计算系统可伸缩性的一项重要技术.介绍了数据广播的体系结构,提出了构建数据广播模型的关键问题,对数据广播调度算法进行了比较详细的分析.     

航空广告:实证、隐喻和目的地形象的建构

航空广告不仅推广了航空公司,也建构了目的地形象。它是社会经济的晴雨表,反映航空业、旅游业和广告业之间的互动关系。航空广告的标题、文案、口号、图片、创意等具有独特的编码和诉求特点,表现出航空广告与目的地形象广告之间的同构性,说明了航空广告对目的地形象建构的一致性原则和神圣化模式。航空广告还隐含着飞行与旅游、旅行的隐喻关系、当代网络和全球化的神化、娱乐的消费主义形态、微笑的女性主义含义等多种意象。     

中国内地航空公司产出的有效性研究

航空公司产出的有效性是航空公司投入人、财、物等资源所产生的效益。提高航空公司产出的有效性 ,需要航空公司把握航空运输市场要素及其特性 ,通过各种资源的优化配置 ,有效开发与利用 ,提高航空公司的运作效率 ,实现要素及其结构优化。科学的市场定位和产品设计 ,重视客户关系管理 ,以及贯彻以人为本的科学发展观 ,是提高航空公司产出的有效性的战略选择。     

A Tighter Extra-Resource Analysis of Online Deadline Scheduling

This paper is concerned with online algorithms for scheduling jobs with deadlines on a single processor. It has been known for long that unless the system is underloaded, no online scheduling algorithm can be 1-competitive, i.e., matching the performance of the optimal offline algorithm. Nevertheless, recent work has revealed that some online algorithms using a moderately faster processor (or extra processors) can guarantee very competitive performance Kalyanasundaram and Pruhs, 2000 or even be 1-competitive Koo et al., 2002; Lam and To, 2001. This paper takes a further step to investigate online scheduling algorithms with an even higher performance guarantee (i.e., better than 1-competitive algorithms) and in particular, presents an extra-resource analysis of the earliest-deadline-first strategy (EDF) with respect to such a higher performance guarantee.A preliminary version of this paper has been accepted by The Australian Theory Symposium on Computing, 2004.This research was supported in part by Hong Kong RGC Grant HKU-7024/01E.     

Scheduling Truck Arrivals at an Air Cargo Terminal

We consider the scheduling of truck arrivals at an air cargo terminal. By coordinating arrivals of cargo delivery trucks with outbound flight departure schedules, some of the shipments can be transferred directly to the departing flights, while others will be stored at the terminal's storage facility and incur extra handling and storage costs. The objective is to obtain a feasible schedule so as to minimize the total cost of operations. We formulate the problem as a time‐indexed integer program and show that, even with limited number of unloading docks at the terminal, the problem is non‐trivial (NP‐hard in the strong sense). Our solution method includes an exact solution procedure to determine an optimal unloading sequence for the shipments carried by each truck, together with a Lagrangian relaxation‐based heuristic for assigning trucks to truck docks and determining truck arrival times. We conducted computational experiments to test the performance of our solution method. Computational results show that our method can generate near‐optimal solutions efficiently. Our simulation results indicate that the scheduling approach proposed in this paper has the potential to generate significant cost savings over a first‐come, first‐served approach currently used at the air cargo terminal that we observed.     

Intelligent Procedures for Intra‐Day Updating of Call Center Agent Schedules

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra‐day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade‐off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.